We would like to acknowledge funding from the United States Department of Agriculture-Agricultural Research Service and from the National Science Foundation (IOS 1025881 and IOS 1361554). We thank R. Caspers for greenhouse maintenance and plant care. We also thank the University of Minnesota Genomics Center, where the Illumina library preparations and sequencing were performed. We are also grateful for the comments from the journal editors and four anonymous reviewers that further strengthened our manuscript. We also thank OECD for a fellowship to SK to integrate these protocols for collaborative projects with colleagues in Japan.

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The authors declare that they have no competing interests.
Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. USDA is an equal opportunity provider and employer.

To date, most organellar sequencing studies center on traditional DC methods to enrich for specific DNA. Methods to isolate organelles from diverse plants have been described, including moss40; monocots such as wheat15 and oats11; and dicots such as arabidopsis11, sunflower17, and rapeseed14. Most protocols focus on leaf tissue13,14,15,16,17, with some having been adapted for a variety of tissue types, including seeds11. The isolation of organelles from protoplasts has also been demonstrated41. However, this not amenable to all systems, nor is it feasible when the tissue of interest is limited. Many of these organellar isolation methods were designed to recover intact organelles for specific experiments, such as physiological studies. These protocols are cumbersome and typically require the use of density gradients, such as sucrose or Percoll gradients, which are very efficient at isolating specific organellar fractions but require a large tissue input (i.e., in excess of 5 g and upwards of kilograms, depending on the tissue type). However, the DC method may be optimized to enrich for specific cellular fractions, such as the mitochondria or chloroplast, by changing spin speeds and density gradients. In contrast, the MF approach requires far less starting material (20 mg), but mitochondrial and plastid DNAs will be present per their relative abundances in the tissue used for DNA extraction. Nonetheless, the MF protocol offers an alternative approach for isolating mixed organellar DNA and is particularly beneficial for starting with small amounts of tissue.
To assess sample purity following organelle isolation, most studies to date only use end-point PCR and gel electrophoresis11,12. This gives a fair qualitative measure of sample purity. However, low levels of amplification may not be visualized on an agarose gel. Few reports include more quantitative measures of quality control, such as qPCR14. For a quantitative assessment of DNA sample purity isolated from both methods, we utilized qPCR and sequencing to determine how much nuclear DNA remains in the sample, as well as the relative proportions of mitochondrial versus chloroplast DNA. Both methods evaluated here are efficient at removing nuclear DNA. Both methods yield a mix of mitochondrial and chloroplast DNA, albeit at different proportions.
Growing plants in the dark (etiolation) is reported to help facilitate organellar isolation due to a reduction of phenolics13. However, in this comparison, we did not find an appreciable advantage to working with etiolated tissue over light-grown samples. Although the proportion of specialized chloroplasts will likely be higher when light-grown, the total plastid number, as reflected in the proportion of reads mapping to the chloroplast genome, is unchanged under differing light conditions. Therefore, for downstream functional analyses, such as the assessment of heteroplasmy in different tissues or under different stressors or for expression analyses, we recommend performing genomic sequencing on plants grown under physiologically relevant conditions.
For application with short-read sequencing technologies, both techniques compared here yield adequate DNA quantity and quality. However, to achieve long reads of &#62;20 kb for single-molecule sequencing applications, a greater amount of higher-quality DNA is necessary. For instance, ideally, &#62; 1 &#181;g of pure organellar wheat DNA with a molecular weight &#62;20 kb is necessary for in-house, low-input protocols for 20-kb insert library preparations42. New user-developed, low-input protocols may reduce DNA requirements (i.e., to 50 ng or even less20), but the challenge remains to have high-quality, high-molecular weight DNA going into the library preparations. It is essential that a majority of the DNA is &#62;20 kb, as smaller fragments will be preferentially inserted into the SMRTbell and throw off the size distribution of the library43. We tried a number of homemade DNA extraction protocols and a number of commercial protocols for DNA extraction (not shown). For wheat leaf tissue, the best balance between DNA quantity and quality, particularly length, was obtained using a commercial kit27,29. Depending on the plant species and tissue of interest, alternative extraction protocols may be equally suited or more fruitful. Nonetheless, we conclude that the total extraction of high-molecular weight genomic DNA &#62;50 kb in size, followed by fractionation with the MBD2-Fc pulldown approach28, is amenable to long-read sequencing from limited starting material. Future work should test the limits of the starting material required following fractionation for long-insert library preparation and subsequent long-read sequencing. Critically, this approach could provide a robust method to isolate DNA from a subsample of a single leaf that is suitable for long-read sequencing, without whole-genome amplification. We anticipate that this approach will be easily adaptable to additional tissue types and broadly applicable to other plant species. It will be particularly useful in situations where the tissue amounts are limiting, such as sequencing at individual generations in a crossing scheme or in rarer tissue types.

Genome sequencing is a powerful tool to dissect the underlying genetic basis of important plant traits. Most genome-sequencing studies focus on the nuclear genome content, as the majority of genes are located in the nucleus. However, organellar genomes, including the mitochondria (across eukaryotes) and plastids (in plants; the specialized form, the chloroplast, works in photosynthesis) contribute significant genetic information essential to organismal development, stress response, and overall fitness1. Organellar genomes are typically included in total DNA extractions intended for nuclear genome sequencing, although methods to reduce organelle numbers prior to DNA extraction are also employed2. Many studies have used sequencing results from total gDNA extractions to assemble organellar genomes3,4,5,6,7. However, when the target of the study is to focus on organellar genomes, using the total gDNA increases the sequencing costs because many reads are &#34;lost&#34; to the nuclear DNA sequences, particularly in plants with large nuclear genomes. Moreover, due to the duplication and transfer of organellar sequences into the nuclear genome and between organelles, resolving the correct mapping position of sequencing reads to the proper genome is bioinformatically challenging2,8. The purification of organellar genomes from the nuclear genome is one strategy to reduce these problems. Further bioinformatics strategies may be used to separate reads that map to regions of homology between the mitochondria and chloroplasts.
While the organellar genomes from many plant species have been sequenced, little is known about the breadth of organellar genome diversity available in wild populations or in cultivated breeding pools. Organellar genomes are also known to be dynamic molecules that undergo significant structural rearrangement due to recombination between repeat sequences9. Moreover, multiple copies of the organellar genome are contained within each organelle, and multiple organelles are contained within each cell. Not all copies of these genomes are identical, which is known as heteroplasmy. In contrast to the canonical picture of &#34;master circles,&#34; there is now growing evidence for a more complex picture of organellar genome structures, including sub-genomic circles, linear chromosomes, linear concatamers, and branched structures10. The assembly of plant organellar genomes is further complicated by their relatively large sizes and substantial inverted and direct repeats.
Traditional protocols for organellar isolation, DNA purification, and subsequent genome sequencing are often cumbersome and require large volumes of tissue input, with several grams to upwards of hundreds of grams of young leaf tissue necessary as a starting point11,12,13,14,15,16,17. This makes organellar genome sequencing inaccessible when tissue is limited. In some situations, seed amounts are limited, such as when it is necessary to sequence on a generational basis or in male sterile lines that have to be maintained via crossing. In these situations, organellar DNA can be purified and then subjected to whole-genome amplification. However, whole-genome amplification can introduce significant sequencing bias, which is a particular problem when assessing structural variation, sub-genomic structures, and heteroplasmy levels18. Recent advances in library preparation for short-read sequencing technologies have overcome low-input barriers to avoid whole-genome amplification. For example, the Illumina Nextera XT library preparation kit allows for as little as 1 ng of DNA to be used as input19. However, standard library preparations for long-read sequencing applications, such as PacBio or Oxford Nanopore sequencing technologies, still require a relatively high amount of input DNA, which can pose a challenge for organellar genome sequencing. Recently, new user-made, long-read sequencing protocols have been developed to reduce the input amounts and to help facilitate genome sequencing in samples where obtaining microgram-quantities of DNA is difficult20,21. However, obtaining high-molecular weight, pure organellar fractions to feed into these library preparations remains a challenge.
We sought to compare and optimize organellar DNA enrichment and isolation methods suitable for NGS without the need of whole-genome amplification. Specifically, our goal was to determine best practices to enrich for high-molecular weight organellar DNA from limited starting materials, such as a subsample of a leaf. This work presents a comparative analysis of methods to enrich for organellar DNA: (1) a modified, traditional differential centrifugation protocol versus (2) a DNA fractionation protocol based on the use of a commercially available DNA CpG-methyl-binding domain protein pulldown approach22 applied to plant tissue23. We recommend best practices for the isolation of organellar DNA from wheat leaf tissue, which may be readily extended to other plants and tissue types.

<table><tbody><tr><td>2-mercaptoethanol (beta-mercaptoethanol; BME)</td><td>Sigma Aldrich</td><td>M3148-100ml</td><td></td></tr><tr><td>2-propanol (Isopropyl alcohol/isopropanol), bioreagent</td><td>Sigma Aldrich</td><td>I9516</td><td></td></tr><tr><td>agarose, Bio-Rad Cetified Megabase agarose</td><td>Bio-Rad</td><td>1613108</td><td></td></tr><tr><td>analytical balance</td><td>Mettler Toledo</td><td>AB54-S</td><td></td></tr><tr><td>balance</td><td>Mettler Toledo</td><td>PB1502-S</td><td></td></tr><tr><td>bovine serum albumin (BSA)</td><td>Sigma Aldrich</td><td>B4287-25G</td><td></td></tr><tr><td>Ceramic grinding cylinders, 3/8in x 7/8in</td><td>SPEX SamplePrep</td><td>2183</td><td></td></tr><tr><td>Cryogenic Blocks compatible with tissue homogenizer for holding 50 mL tubes</td><td>SPEX SamplePrep</td><td>2664</td><td></td></tr><tr><td>DNaseI</td><td>Sigma</td><td>DN25</td><td></td></tr><tr><td>ethanol, absolute</td><td>Decon Laboratories</td><td>2716</td><td></td></tr><tr><td>Ethylenediamine Tetraacetic Acid (EDTA), 0.5 M Solution, pH 8.0</td><td>Fisher</td><td>BP2482-500</td><td></td></tr><tr><td>gel imaging system</td><td></td><td></td><td></td></tr><tr><td>gel stain</td><td></td><td></td><td>Such as GelRed or Ethidium Bromide</td></tr><tr><td>grinding pestle, wide tip for 2 mL conical tubes</td><td></td><td></td><td></td></tr><tr><td>Guanidine-HCl, 8 M solution</td><td>ThermoFisher</td><td>24115</td><td></td></tr><tr><td>LightCycler 480 SYBR Green I Master</td><td>Roche</td><td>4707516001</td><td></td></tr><tr><td>liquid nitrogen</td><td></td><td></td><td></td></tr><tr><td>Lysing enzymes from Trichoderma harzianum</td><td>Sigma</td><td>L1412</td><td></td></tr><tr><td>Magnesium Chloride</td><td>G Bioscience</td><td>24115</td><td></td></tr><tr><td>magnetic rack</td><td>ThermoFisher</td><td>A13346</td><td></td></tr><tr><td>microcentrifuge tubes, LoBind 1.5 mL&amp;nbsp;</td><td>Eppendorf</td><td>22431021</td><td></td></tr><tr><td>microcentrifuge tubes, standard nuclease-free 1.5 mL</td><td>Eppendorf</td><td></td><td></td></tr><tr><td>microcentrifuge, refrigerated</td><td>Sorvall&amp;nbsp;</td><td>Legend X1R</td><td>Or equivalent product, must be capable of reaching at least 18,000 x g with rotors for 50 mL tubes, Oak Ridge tubes, and 1.5 mL tubes</td></tr><tr><td>microcentrifuge, room temperature</td><td>Eppendorf</td><td>5424</td><td>Or equivalent product, must be capable of reaching at least 18,000 x g with rotor for 1.5 mL and 2 mL microcentrifuge tubes</td></tr><tr><td>Microcon DNA Fast Flow Centrifugal Filter Units</td><td>EMD Millipore</td><td>MRCFOR100</td><td></td></tr><tr><td>Miracloth, 1 square per sample cut to fit funnel</td><td>EMD Millipore</td><td>475855</td><td></td></tr><tr><td>NEBNext Microbiome DNA Enrichment Kit</td><td>New England Biolabs</td><td>E2612L</td><td></td></tr><tr><td>parafilm</td><td>Parafilm M</td><td>PM992</td><td></td></tr><tr><td>plastic pots and trays</td><td></td><td></td><td></td></tr><tr><td>polyvinylpyrrolidone (PVP)</td><td>Fisher</td><td>BP431-100</td><td></td></tr><tr><td>Proteinase K</td><td>Qiagen</td><td>19131</td><td></td></tr><tr><td>Pulsed-Field Gel Electrophoresis rig (e.g. CHEF DR III)</td><td>Bio-Rad</td><td>1703697</td><td></td></tr><tr><td>purification beads, Agencourt AMpureXP beads</td><td>Beckman Coulter</td><td>A63881</td><td></td></tr><tr><td>QIAamp DNA Mini Kit</td><td>Qiagen</td><td>51304</td><td></td></tr><tr><td>Qiagen 20/g Genomic Tip DNA Extraction Kit</td><td>Qiagen</td><td>10223</td><td></td></tr><tr><td>Qiagen Buffer EB (elution buffer)</td><td>Qiagen</td><td>19086</td><td></td></tr><tr><td>Qiagen DNA Extraction Buffer Set</td><td>Qiagen</td><td>19060</td><td></td></tr><tr><td>QiaRack</td><td>Qiagen</td><td>19015</td><td></td></tr><tr><td>qPCR machine (e.g. Roche Light Cycler 480)</td><td>Roche</td><td></td><td></td></tr><tr><td>qPCR plate sealing film</td><td>Roche</td><td>4729757001</td><td></td></tr><tr><td>qPCR plate, 96 well plate</td><td>Roche</td><td>4729692001</td><td></td></tr><tr><td>Qubit&amp;nbsp;assay tubes</td><td>Life Technologies</td><td>Q32856</td><td></td></tr><tr><td>Qubit Broad Spectrum assay kit</td><td>Life Technologies</td><td>Q32850</td><td></td></tr><tr><td>Qubit High Sensitivity assay kit</td><td>Life Technologies</td><td>Q32851</td><td></td></tr><tr><td>RNaseA</td><td>Qiagen</td><td>19101</td><td></td></tr><tr><td>Serological pipettes (20 mL) and pipet-aid</td><td>Fisher</td><td>13-678-11</td><td></td></tr><tr><td>Small funnels, 1 per sample</td><td></td><td></td><td></td></tr><tr><td>Sodium Chloride</td><td>Ambion</td><td>AM9759</td><td></td></tr><tr><td>Soft paintbrush, 2 per sample</td><td></td><td></td><td></td></tr><tr><td>SPEX SamplePrep 2010 Geno/Grinder or another type of tissue homogenizer</td><td>SPEX SamplePrep</td><td></td><td>Or another comparable tissue homogenizer. If you do not have access to a tissue homogenizer, then grinding in a pre-chilled mortar and pestle will suffice (see protocol for details). However, a homogenizer will give more consistent results and total homogenization time is reduced.</td></tr><tr><td>Sucrose</td><td>Omnipure</td><td>8550</td><td></td></tr><tr><td>TBE</td><td></td><td></td><td></td></tr><tr><td>thermomixer</td><td></td><td></td><td></td></tr><tr><td>Tris</td><td>Sigma</td><td>T2819-100ml</td><td></td></tr><tr><td>Triton X-100</td><td>Promega</td><td>H5142</td><td></td></tr><tr><td>tube rotater</td><td></td><td></td><td></td></tr><tr><td>tubes, 50 mL conical polypropylene</td><td>Corning</td><td>352070</td><td></td></tr><tr><td>tubes, 50 mL high-speed polypropylene&amp;nbsp;</td><td>ThermoScientific/Nalgene</td><td>3119-0050</td><td>e.g. Nalgene Oakridge tubes or equivalent</td></tr><tr><td>vermiculite</td><td></td><td></td><td></td></tr><tr><td>water bath</td><td></td><td></td><td></td></tr><tr><td>water, sterile and certified Nuclease-free&amp;nbsp;</td><td>Fisher</td><td>1481</td><td></td></tr><tr><td>water, sterile milliQ</td><td></td><td></td><td></td></tr></tbody></table>

optimization and comparative analysis of plant organellar dna enrichment methods suitable for next-generation sequencing

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic fragments. Organellar genomes also exist in admixtures within a given cell or tissue type (heteroplasmy), and an abundance of subtypes may change throughout development or when under stress (sub-stoichiometric shifting). Next-generation sequencing (NGS) technologies are required to obtain deeper understanding of organellar genome structure and function. Traditional sequencing studies use several methods to obtain organellar DNA: (1) If a large amount of starting tissue is used, it is homogenized and subjected to differential centrifugation and/or gradient purification. (2) If a smaller amount of tissue is used (i.e., if seeds, material, or space is limited), the same process is performed as in (1), followed by whole-genome amplification to obtain sufficient DNA. (3) Bioinformatics analysis can be used to sequence the total genomic DNA and to parse out organellar reads. All these methods have inherent challenges and tradeoffs. In (1), it may be difficult to obtain such a large amount of starting tissue; in (2), whole-genome amplification could introduce a sequencing bias; and in (3), homology between nuclear and organellar genomes could interfere with assembly and analysis. In plants with large nuclear genomes, it is advantageous to enrich for organellar DNA to reduce sequencing costs and sequence complexity for bioinformatics analyses. Here, we compare a traditional differential centrifugation method with a fourth method, an adapted CpG-methyl pulldown approach, to separate the total genomic DNA into nuclear and organellar fractions. Both methods yield sufficient DNA for NGS, DNA that is highly enriched for organellar sequences, albeit at different ratios in mitochondria and chloroplasts. We present the optimization of these methods for wheat leaf tissue and discuss major advantages and disadvantages of each approach in the context of sample input, protocol ease, and downstream application.

Watch this Scientific Journal Video about Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing at JoVE.com

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

The comparison and optimization of two plant organellar DNA enrichment methods are presented: traditional differential centrifugation and fractionation of the total gDNA based on methylation status. We assess the resulting DNA quantity and quality, demonstrate performance in short-read next-generation sequencing, and discuss the potential for use in long-read single-molecule sequencing.

Plant organellar genomes contain large, repetitive elements that may undergo pairing or recombination to form complex structures and/or sub-genomic ...

optimization-comparative-analysis-plant-organellar-dna-enrichment

Nanyang Technological University

Research

JoVE Journal

Genetics

12.8K Views.  United States Department of Agriculture-Agricultural Research Service.  De vergelijking en optimalisatie van twee organellaire DNA-verrijkingsmethoden worden voorgesteld: traditionele differentiële centrifugatie en fractionering van het totale gDNA op basis van methyleringsstatus. We beoordelen de resulterende DNA-hoeveelheid en kwaliteit, tonen de prestaties aan bij korte-leesvolgorde-sequencing, en bespreken het potentieel voor gebruik bij langlezen single-molecule sequencing. 

Video: Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

Purification of High Molecular Weight Genomic DNA from Powdery Mildew for Long-Read Sequencing

The powdery mildew fungi are a group of economically important fungal plant pathogens. Relatively little is known about the molecular biology and genetics of these pathogens, in part due to a lack of well-developed genetic and genomic resources. These organisms have large, repetitive genomes, which have made genome sequencing and assembly prohibitively difficult. Here, we describe methods for the collection, extraction, purification and quality control assessment of high molecular weight genomic DNA from one powdery mildew species, Golovinomyces cichoracearum. The protocol described includes mechanical disruption of spores followed by an optimized phenol/chloroform genomic DNA extraction. A typical yield was 7 &#181;g DNA per 150 mg conidia. The genomic DNA that is isolated using this procedure is suitable for long-read sequencing (i.e., &#62; 48.5 kbp). Quality control measures to ensure the size, yield, and purity of the genomic DNA are also described in this method. Sequencing of the genomic DNA of the quality described here will allow for the assembly and comparison of multiple powdery mildew genomes, which in turn will lead to a better understanding and improved control of this agricultural pathogen.

Described here is a method for the extraction, purification, and quality control of genomic DNA from the obligate biotrophic fungal pathogen, powdery mildew, for use in long-read genome sequencing.

The powdery mildew fungi are a group of economically important fungal plant pathogens. Relatively little is known about the molecular biology and genetics ...

Robust DNA Isolation and High-throughput Sequencing Library Construction for Herbarium Specimens

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with a number of challenges including sample preservation quality, degraded DNA, and destructive sampling of rare specimens. In order to more effectively use herbarium material in large sequencing projects, a dependable and scalable method of DNA isolation and library preparation is needed. This paper demonstrates a robust, beginning-to-end protocol for DNA isolation and high-throughput library construction from herbarium specimens that does not require modification for individual samples. This protocol is tailored for low quality dried plant material and takes advantage of existing methods by optimizing tissue grinding, modifying library size selection, and introducing an optional reamplification step for low yield libraries. Reamplification of low yield DNA libraries can rescue samples derived from irreplaceable and potentially valuable herbarium specimens, negating the need for additional destructive sampling and without introducing discernible sequencing bias for common phylogenetic applications. The protocol has been tested on hundreds of grass species, but is expected to be adaptable for use in other plant lineages after verification. This protocol can be limited by extremely degraded DNA, where fragments do not exist in the desired size range, and by secondary metabolites present in some plant material that inhibit clean DNA isolation. Overall, this protocol introduces a fast and comprehensive method that allows for DNA isolation and library preparation of 24 samples in less than 13 h, with only 8 h of active hands-on time with minimal modifications.

This article demonstrates a detailed protocol for DNA isolation and high-throughput sequencing library construction from herbarium material including rescue of exceptionally poor-quality DNA.

Herbaria are an invaluable source of plant material that can be used in a variety of biological studies. The use of herbarium specimens is associated with ...

Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

Next-generation sequencing (NGS) is quickly revolutionizing how research into the genetic determinants of constitutional disease is performed. The technique is highly efficient with millions of sequencing reads being produced in a short time span and at relatively low cost. Specifically, targeted NGS is able to focus investigations to genomic regions of particular interest based on the disease of study. Not only does this further reduce costs and increase the speed of the process, but it lessens the computational burden that often accompanies NGS. Although targeted NGS is restricted to certain regions of the genome, preventing identification of potential novel loci of interest, it can be an excellent technique when faced with a phenotypically and genetically heterogeneous disease, for which there are previously known genetic associations. Because of the complex nature of the sequencing technique, it is important to closely adhere to protocols and methodologies in order to achieve sequencing reads of high coverage and quality. Further, once sequencing reads are obtained, a sophisticated bioinformatics workflow is utilized to accurately map reads to a reference genome, to call variants, and to ensure the variants pass quality metrics. Variants must also be annotated and curated based on their clinical significance, which can be standardized by applying the American College of Medical Genetics and Genomics Pathogenicity Guidelines. The methods presented herein will display the steps involved in generating and analyzing NGS data from a targeted sequencing panel, using the ONDRISeq neurodegenerative disease panel as a model, to identify variants that may be of clinical significance.

Targeted next-generation sequencing is a time- and cost-efficient approach that is becoming increasingly popular in both disease research and clinical diagnostics. The protocol described here presents the complex workflow required for sequencing and the bioinformatics process used to identify genetic variants that contribute to disease.

Next-generation sequencing (NGS) is quickly revolutionizing how research into the genetic determinants of constitutional disease is performed. The ...

Exploring the Root Microbiome: Extracting Bacterial Community Data from the Soil, Rhizosphere, and Root Endosphere

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to abiotic stresses and diseases. As the plant microbiome can be highly complex, low-cost, high-throughput methods such as amplicon-based sequencing of the 16S rRNA gene are often preferred for characterizing its microbial composition and diversity. However, the selection of appropriate methodology when conducting such experiments is critical for reducing biases that can make analysis and comparisons between samples and studies difficult. This protocol describes in detail a standardized methodology for the collection and extraction of DNA from soil, rhizosphere, and root samples. Additionally, we highlight a well-established 16S rRNA amplicon sequencing pipeline that allows for the exploration of the composition of bacterial communities in these samples, and can easily be adapted for other marker genes. This pipeline has been validated for a variety of plant species, including sorghum, maize, wheat, strawberry, and agave, and can help overcome issues associated with the contamination from plant organelles.

Here, we describe a protocol to obtain amplicon sequence data of soil, rhizosphere, and root endosphere microbiomes. This information can be used to investigate the composition and diversity of plant-associated microbial communities, and is suitable for the use with a wide range of plant species.

The intimate interaction between plant host and associated microorganisms is crucial in determining plant fitness, and can foster improved tolerance to ...

Optimization for Sequencing and Analysis of Degraded FFPE-RNA Samples

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding of the basis of various diseases as well as resistance and/or susceptibility mechanisms. However, FFPE tissues, which represent the most common method for preserving tissue morphology in clinical specimens, are not the best sources for gene expression profiling analysis. The RNA obtained from such samples is often degraded, fragmented, and chemically modified, which leads to suboptimal sequencing libraries. In turn, these generate poor quality sequence data that may not be reliable for gene expression analysis and mutation discovery. In order to make the most of FFPE samples and obtain the best possible data from low quality samples, it is important to take certain precautions while planning experimental design, preparing sequencing libraries, and during data analysis. This includes the use of appropriate metrics for precise sample quality control (QC), identifying the best methods for various steps during the sequencing library generation, and careful library QC. In addition, applying correct software tools and parameters for sequence data analysis is critical in order to identify artifacts in RNA-seq data, filter out contamination and low quality reads, assess uniformity of gene coverage, and measure the reproducibility of gene expression profiles among biological replicates. These steps can ensure high accuracy and reproducibility for profiling of very heterogeneous RNA samples. Here we describe the various steps for sample QC, library preparation and QC, sequencing, and data analysis that can help to increase the amount of useful data obtained from low quality RNA, such as that obtained from FFPE-RNA tissues.

This method describes the steps to improve the quality and quantity of sequence data that can be obtained from formalin-fixed paraffin-embedded (FFPE) RNA samples. We describe the methodology to more accurately assess the quality of FFPE-RNA samples, prepare sequencing libraries, and analyze the data from FFPE-RNA samples.

Gene expression analysis by RNA sequencing (RNA-seq) enables unique insights into clinical samples that can potentially lead to mechanistic understanding ...

DNA Barcoding for Medicinal Plants: Identification and Phylogenetic Analysis

Application of DNA Barcoding to Identify Medicinal Plants

Medicinal plants are valuable resources globally and are used worldwide to maintain health and treat disease; however, the presence of adulteration obstructs their development. DNA barcoding, a technique for species identification by standard DNA regions, facilitates prompt and accurate identification of traditional medicinal plants. The process of DNA barcoding entails six basic steps: 1) processing the medicinal plants, 2) extracting high-quality total DNA from the medicinal plants using centrifugal column method, 3) amplifying target DNA region internal transcribed spacer 2 (ITS2) with universal primers of plants and performing Sanger sequencing, 4) splicing and aligning sequence to obtain the target sequence, 5) matching the barcode sequence against the barcode library for identification, 6) aligning sequence, comparing intraspecific and interspecific variation, constructing phylogenetic neighbor-joining tree. As shown in the results, the universal primer can amplify the target region. Basic Local Alignment Search Tool (BLAST) demonstrates the percentage identified was 100%, and the neighbor-joining tree demonstrates that the splicing sequences were clustered with the A. sinensis OR879715.1 clade, and the clade support value is 100. This protocol provides a reference for applying DNA barcoding technology as an effective method to identify medicinal plants and adulterants.

Author Spotlight: Harnessing DNA Barcode Technology to Enhance the Efficiency of Medicinal Plant Identification

The present protocol describes the use of DNA barcoding technology to authenticate plant-based medicinal materials, and the medicinal plant Angelica sinensis (Oliv.) Diels was identified as an example.

Medicinal plants are valuable resources globally and are used worldwide to maintain health and treat disease; however, the presence of adulteration ...

Collection and Extraction of Saliva DNA for Next Generation Sequencing

The preferred source of DNA in human genetics research is blood, or cell lines derived from blood, as these sources yield large quantities of high quality DNA. However, DNA extraction from saliva can yield high quality DNA with little to no degradation/fragmentation that is suitable for a variety of DNA assays without the expense of a phlebotomist and can even be acquired through the mail. However, at present, no saliva DNA collection/extraction protocols for next generation sequencing have been presented in the literature. This protocol optimizes parameters of saliva collection/storage and DNA extraction to be of sufficient quality and quantity for DNA assays with the highest standards, including microarray genotyping and next generation sequencing.

DNA extraction from saliva can provide a readily available source of high molecular weight DNA, with little to no degradation/fragmentation. This protocol provides optimized parameters for saliva collection/storage and DNA extraction to be of sufficient quality and quantity for downstream DNA assays with high quality requirements.

The preferred source of DNA in human genetics research is blood, or cell lines derived from blood, as these sources yield large quantities of high quality ...

Medicine

Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies

All next-generation sequencing (NGS) procedures include assays performed at the laboratory bench (&#34;wet bench&#34;) and data analyses conducted using bioinformatics pipelines (&#34;dry bench&#34;). Both elements are essential to produce accurate and reliable results, which are particularly critical for clinical laboratories. Targeted NGS technologies have increasingly found favor in oncology applications to help advance precision medicine objectives, yet the methods often involve disconnected and variable wet and dry bench workflows and uncoordinated reagent sets. In this report, we describe a method for sequencing challenging cancer specimens with a 21-gene panel as an example of a comprehensive targeted NGS system. The system integrates functional DNA quantification and qualification, single-tube multiplexed PCR enrichment, and library purification and normalization using analytically-verified, single-source reagents with a standalone bioinformatics suite. As a result, accurate variant calls from low-quality and low-quantity formalin-fixed, paraffin-embedded (FFPE) and fine-needle aspiration (FNA) tumor biopsies can be achieved. The method can routinely assess cancer-associated variants from an input of 400 amplifiable DNA copies, and is modular in design to accommodate new gene content. Two different types of analytically-defined controls provide quality assurance and help safeguard call accuracy with clinically-relevant samples. A flexible &#34;tag&#34; PCR step embeds platform-specific adaptors and index codes to allow sample barcoding and compatibility with common benchtop NGS instruments. Importantly, the protocol is streamlined and can produce 24 sequence-ready libraries in a single day. Finally, the approach links wet and dry bench processes by incorporating pre-analytical sample quality control results directly into the variant calling algorithms to improve mutation detection accuracy and differentiate false-negative and indeterminate calls. This targeted NGS method uses advances in both wetware and software to achieve high-depth, multiplexed sequencing and sensitive analysis of heterogeneous cancer samples for diagnostic applications.

An integrated system for targeted next-generation sequencing of oncology specimens is described. This cross-platform system is optimized for low-quality and low-quantity tumor biopsies, accommodates low DNA inputs, includes well-characterized multi-variant controls, and features a novel variant caller that is informed by quantitative pre-analytical quality control measures.

All next-generation sequencing (NGS) procedures include assays performed at the laboratory bench (&#34;wet bench&#34;) and data analyses conducted using ...

Fluorescence-microscopy Screening and Next-generation Sequencing: Useful Tools for the Identification of Genes Involved in Organelle Integrity

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the subcellular distribution of a specific tagged fluorescent marker in the secretory pathway. Arabidopsis is a powerful biological model for genetic studies because of its genome size, generation time, and conservation of molecular mechanisms among kingdoms. The array genotyping as an approach to map the mutation in alternative to the traditional method based on molecular markers is advantageous because it is relatively faster and may allow the mapping of several mutants in a really short time frame. This method allows the identification of proteins that can influence the integrity of any organelle in plants. Here, as an example, we propose a screen to map genes important for the integrity of the endoplasmic reticulum (ER). Our approach, however, can be easily extended to other plant cell organelles (for example see1,2), and thus represents an important step toward understanding the molecular basis governing other subcellular structures.

A fundamental quest in cell biology is to define the mechanisms that underlie the identity of the organelles that make eukaryotic cells. Here we propose a method to identify the genes responsible for the morphological and functional integrity of plant organelles using fluorescence microscopy and next-generation sequencing tools.

This protocol describes a fluorescence microscope-based screening of Arabidopsis seedlings and describes how to map recessive mutations that alter the ...

Biology

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

The widespread use of Next Generation Sequencing has opened up new avenues for cancer research and diagnosis. NGS will bring huge amounts of new data on cancer, and especially cancer genetics. Current knowledge and future discoveries will make it necessary to study a huge number of genes that could be involved in a genetic predisposition to cancer. In this regard, we developed a Nextera design to study 11 complete genes involved in DNA damage repair. This protocol was developed to safely study 11 genes (ATM, BARD1, BRCA1, BRCA2, BRIP1, CHEK2, PALB2, RAD50, RAD51C, RAD80, and TP53) from promoter to 3&#39;-UTR in 24 patients simultaneously. This protocol, based on transposase technology and gDNA enrichment, gives a great advantage in terms of time for the genetic diagnosis thanks to sample multiplexing. This protocol can be safely used with blood gDNA.

gDNA Enrichment by a Transposase-based Technology for NGS Analysis of the Whole Sequence of BRCA1, BRCA2, and 9 Genes Involved in DNA Damage Repair

gDNA enrichment for NGS sequencing is an easy and powerful tool for the study of constitutional mutations. In this article, we present the procedure to analyse simply the complete sequence of 11 genes involved in DNA damage repair.

The widespread use of Next Generation Sequencing has opened up new avenues for cancer research and diagnosis. NGS will bring huge amounts of new data on ...

Optimization and Comparative Analysis of Plant Organellar DNA Enrichment Methods Suitable for Next-generation Sequencing

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